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Commit de2a6dd

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[Doc] Updated the doc for the Python upgrade
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‎README.md

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@@ -10,13 +10,14 @@ produces
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[Docker images](https://hub.docker.com/repository/docker/infrahelpers/python-jupyter),
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which provide ready-to-use Artificial Intelligence (AI) / Machine Learning (ML)
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Python Jupyter environments on a few well known and stable Linux distributions
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(_e.g._, [CentOS 8](https://wiki.centos.org/Manuals/ReleaseNotes/CentOSLinux8),
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(_e.g._, [CentOS 9 Stream](https://centos.org/stream9/),
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[CentOS 8 Stream](https://wiki.centos.org/Manuals/ReleaseNotes/CentOSLinux8),
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[CentOS 7](https://wiki.centos.org/Manuals/ReleaseNotes/CentOS7),
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[Debian 11 (Bookworm)](https://www.debian.org/releases/bookworm/),
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[Debian 11 (Bullseye)](https://www.debian.org/releases/bullseye/),
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[Debian 10 (Buster)](https://www.debian.org/releases/buster/),
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[Ubuntu 20.04 LTS (Focal Fossa)](https://releases.ubuntu.com/20.04/),
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[Ubuntu 18.04 LTS (Bionic Beaver)](https://releases.ubuntu.com/18.04/) and
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[Ubuntu 16.04 LTS (Xenial Xerus)](https://releases.ubuntu.com/16.04/)).
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[Ubuntu 22.04 LTS (Jammy Jellyfish)](https://releases.ubuntu.com/22.04/),
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[Ubuntu 20.04 LTS (Focal Fossa)](https://releases.ubuntu.com/20.04/) and
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[Ubuntu 18.04 LTS (Bionic Beaver)](https://releases.ubuntu.com/18.04/)).
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The Docker images just add some Jupyter notebook and data set samples
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on top of other
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* Production-ready Python cloud images:
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+ On GitHub: https://github.com/cloud-helpers/cloud-python-images
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+ On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers/cloud-python
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* Production-ready Data Processing Pipelines (DPP) images:
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+ On GitHub: https://github.com/data-engineering-helpers/dpp-images
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+ On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers/dpp
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* General purpose C++/Python images:
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+ On GitHub: https://github.com/cpp-projects-showcase/docker-images
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+ On Docker Hub: https://hub.docker.com/repository/docker/cpppythondevelopment/base
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+ On Docker Hub: https://hub.docker.com/repository/docker/infrahelpers/cpppython
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* Native Docker Python images:
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+ On GitHub: https://github.com/docker-library/python
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+ On Docker Hub: https://hub.docker.com/_/python
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# Simple use
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* Download the Docker image for your preferred Linux distribution (where
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`<linux-distrib>` is one of `centos8`, `centos7`, `debian11`, `debian10`,
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`ubuntu2004`, `ubuntu1804`or `ubuntu1604`):
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`<linux-distrib>` is one of `centos9`, `centos8`, `centos7`, `debian12`,
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`debian11`, `ubuntu2204`, `ubuntu2004`or `ubuntu1804`):
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```bash
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$ docker pull infrahelpers/python-jupyter:<linux-distrib>
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```
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## With the Jupyter notebook and data set samples provided by the Docker images
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* Launch Jupyter Lab within the Docker image (where `<port>` corresponds
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to the local port on which Jupyter Lab is launched; the default is 8888):
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to the local port on which Jupyter Lab is launched; the default is `8888`):
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```bash
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$ docker run -d -p <port>:8888 infrahelpers/python-jupyter:<linux-distrib>
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```
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## With your own Jupyter notebooks and data sets
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* Launch Jupyter Lab within the Docker image (where `<port>` corresponds
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to the local port on which Jupyter Lab is launched; the default is 8888):
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to the local port on which Jupyter Lab is launched; the default is `8888`):
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```bash
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$ docker run -d -p <port>:8888 -v ${PWD}/notebook/induction:/notebook -v ${PWD}/data/induction:/data infrahelpers/python-jupyter:<linux-distrib>
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```
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## Interact with Jupyter Lab in a Web browser
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Jupyter Lab (run from the Docker image) is now available on the Web browser:
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http://localhost:8888
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Note that the port (8888 by default) may be changed as per your convenience.
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Note that the port (`8888` by default) may be changed as per your convenience.
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# Build your own Docker image
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* Clone the
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$ cd docker-python-jupyter
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```
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* Build the Docker image (the `--squash` option is only available on
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[Docker Edge](http://docs.docker.com/edge/), as of end of 2018):
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* Build the Docker image:
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```bash
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$ docker build -t infrahelpers/python-jupyter:<linux-distrib> --squash <linux-distrib>/
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$ docker build -t infrahelpers/python-jupyter:<linux-distrib> <linux-distrib>/
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$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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infrahelpers/python-jupyter linux-distrib 33a1ad533140 About a minute ago 2.29GB
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[a change on GitHub](https://github.com/machine-learning-helpers/docker-python-jupyter/commits/master))
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```bash
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$ docker login
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$ docker push infrahelpers/python-jupyter-manual:<linux-distrib>
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$ docker push infrahelpers/python-jupyter:<linux-distrib>
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```
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* Shutdown the Docker image
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```bash
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$ docker ps
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CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
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7b69efc9dc9a ai/python-jupyter:centos7 "/bin/sh -c 'pipenv ..." 48 seconds ago Up 47 seconds 0.0.0.0:9000->8888/tcp vigilant_merkle
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7b69efc9dc9a ai/python-jupyter:centos9 "/bin/sh -c 'pipenv ..." 48 seconds ago Up 47 seconds 0.0.0.0:9000->8888/tcp vigilant_merkle
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$ docker kill vigilant_merkle
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vigilant_merkle
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$ docker ps

‎ubuntu2204/Dockerfile

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#
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# Python Jupyter notebooks for Artificial Intelligence (AI) / Machine Learning (ML) on Ubuntu 22.04 LTS (Focal Fossa)
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# Python Jupyter notebooks for Artificial Intelligence (AI) / Machine Learning (ML) on Ubuntu 22.04 LTS
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#
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# Source: https://github.com/machine-learning-helpers/docker-python-jupyter/blob/master/ubuntu2204/Dockerfile
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#

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